import os
import sys

import scipy.io as sio
import tensorflow as tf
from spektral.layers import GCNConv, GeneralConv
from spektral.utils import sp_matrix_to_sp_tensor
from tensorflow.keras.layers import (Conv2D, Conv2DTranspose, Dense, DepthwiseConv2D,
                                     GlobalAveragePooling2D, Layer,
                                     LayerNormalization, Flatten, Reshape, UpSampling2D)

sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))


class Smoother(tf.keras.Model):
    def __init__(self, ):
        super().__init__()
        self.a = sp_matrix_to_sp_tensor(sio.loadmat("custom_utils/ssmpl0.mat")['L'].tocoo())
        self.conv1 = GCNConv(16, activation='tanh', use_bias=False)
        self.conv2 = GCNConv(3, activation='tanh', use_bias=False)
        # self.conv3 = GCNConv(512, activation='tanh', use_bias=False)
        # self.conv4 = GCNConv(512, activation='tanh', use_bias=False)
        # self.conv5 = GCNConv(64, activation='tanh', use_bias=False)
        self.conv6 = GCNConv(3, activation='tanh', use_bias=False)

    def call(self, inputs, training=None):
        x = inputs
        x = self.conv1([x, self.a], training=training)
        x = self.conv2([x, self.a], training=training)
        # x = self.conv3([x, self.a], training=training)
        # x = self.conv4([x, self.a], training=training)
        # x = self.conv5([x, self.a], training=training)
        x = self.conv6([x, self.a], training=training)
        return x